Last modified: February 2018

SYNTHIA, The  SYNTHetic collection of Imagery and Annotations, is a dataset that has been generated with the purpose of aiding semantic segmentation and related scene understanding problems in the context of driving scenarios. SYNTHIA consists of a collection of photo-realistic frames rendered from a virtual city and comes with precise pixel-level semantic annotations.


  • Large volume of data & groundtruth: +200,000 HD images from video streams and +20,000 HD images from independent snapshots

  • Scene diversity: European style town, modern city, highway and green areas

  • Variety of dynamic objects: cars, pedestrians and cyclists

  • Multiple seasons: dedicated themes for winter, fall, spring and summer

  • Lighting conditions and weather: dynamic lights and shadows, several day-time modes, rain mode and night mode

  • Sensor simulation: 8 RGB cameras forming a binocular 360º camera, 8 depth sensors

Recent News

Best industrial paper award at BMVC2017

The paper ‘Slanted stixels: Representing San Francisco’s Steepest Streets‘ has been awarded the best industrial paper award at the British Machine Vision Conference 2017 in London. This paper is the result of the work produced by CVC, UAB and Daimler, more specifically authors Daniel Hernández, Lukas Schneider, Dr. Antonio Espinosa, Dr. David Vázquez, Dr. Uwe

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SYNTHIA-SF is now available

The dataset SYNTHIA-SF used in our BMVC’17 paper is now available. A dataset with more than 2,000 driving images, with Cityscapes compatible semantic labels.

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Download procedure

We have changed the download procedure. Now when you request to download a sequence you will receive an email with a link to a txt file. This txt file has the links to download the sequence. The links are .rar file parts. You can download them directly or with you favorite download manager. Once downloaded

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In press